Fuzzy solution in fuzzy linear programming problems

Conventional mathematical programming problems are to maximize an objective function subject to constraints. In the real decision problems, however, a satisfaction criterion might be more useful than a criterion of maximizing an objective function in making the decision under fuzzy constraints. From...

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Bibliographic Details
Published in:IEEE transactions on systems, man, and cybernetics Vol. SMC-14; no. 2; pp. 325 - 328
Main Authors: Tanaka, Hideo, Asai, Kiyoji
Format: Journal Article
Language:English
Published: New York, NY IEEE 01.03.1984
Institute of Electrical and Electronics Engineers
Subjects:
Aerospace electronics
Applied sciences
Bismuth
Cybernetics
Exact sciences and technology
Fuzzy sets
Learning automata
Linear programming
Mathematical programming
Operational research and scientific management
Operational research. Management science
Optimization
Linear programming
Fuzzy decision
Decision theory
Mathematical programming
ISSN:0018-9472, 2168-2909
Online Access:Get full text
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Summary:Conventional mathematical programming problems are to maximize an objective function subject to constraints. In the real decision problems, however, a satisfaction criterion might be more useful than a criterion of maximizing an objective function in making the decision under fuzzy constraints. From this point, fuzzy linear programming problems are discussed in which both constraints and objective functions are assumed to be of fuzzy inequalities. The problem is to obtain a fuzzy solution such that the fuzzy inequalities hold. In a fuzzy solution the greatest possibility distribution of decision is determined. Our aim is to find out how fuzzy solution will be possible. This problem can be reduced to the conventional linear programming problem so that this fuzzy linear programming problem can be easily solved by the ordinary algorithms of linear programming.
ISSN:0018-9472
2168-2909
DOI:10.1109/TSMC.1984.6313219